Modeling Collision Avoidance Actions Using Environment-Vulnerability-Decision-Technology Framework

The population of Anthropogenic Space Objects (ASOs) in Earth’s orbit is steadily increasing. As of the start of 2023, the US Space Surveillance Network is tracking over 27,000 ASOs larger than a smartphone. From the space Collision Avoidance (COLA) perspective, workload and complexity heavily increases as the number of probable collisions between active spacecraft and ASOs rises. To choose an optimal architecture for COLA operations in the future, a need for a Decision Support System (DSS) is unavoidable. This paper outlines the first application of the Environment-Vulnerability-Decision-Technology (EVDT) framework in the space domain, to develop a prototype DSS for COLA operations. EVDT is a systems engineering framework that accounts for the interdependent relationships and feedback loops within complex systems to promote sustainable development. The framework considers social, environmental, and economic factors and creates a DSS for high uncertainty and multi-stakeholder scenarios. While EVDT has been successfully demonstrated previously using Earth observation systems for terrestrial applications, this paper presents the first application of the framework to a space environment. As a case study of an operational conjunction assessment team, the authors consider the publicly documented operations of NASA Conjunction Assessment Risk Analysis (CARA) which provides conjunction and risk analysis services to NASA’s uncrewed spacecraft before and after launch. In this paper, the authors have developed a computer model called COLA-EVDT using the EVDT framework to model the main in-space COLA operational steps by identifying four interconnected system components: the "Environment" component which models possible conjunctions between specified primary spacecraft and other ASOs; the "Vulnerability" component which models the socioeconomic impact of a conjunction, calculated as a normalized value; the "Decision" component which models the possible actions taken by the COLA operators in response to receiving Conjunction Data Messages (CDMs); and the "Technology" component which models the data outputs of Space Situational Awareness (SSA) providers. Several active NASA Earth Observing System (EOS) satellites are considered as the primary objects for conjunction analysis. COLA-EVDT uses space catalogs obtained from Space-Track, geometrically filters irrelevant ASOs, propagates remaining objects, and performs volumetric screening to detect conjunctions. By utilizing publicly released CARA software, the model generates CDMs and calculates the vulnerability value of each conjunction event. The model is developed using an open-source, modular architecture so that each component of COLA-EVDT is customizable by the user to analyze various situations. The results presented in the paper demonstrate that employing EVDT in an interactive data-driven DSS can effectively highlight the impact of various risk mitigation strategies and distinct SSA data sources. This paper represents the first step in the development of a comprehensive space EVDT framework that simultaneously considers physical and socioeconomic factors informing collision avoidance.